Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling.

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Title: Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling.
Authors: Swallow B; School of Mathematics and Statistics, University of Glasgow, Glasgow, UK; Scottish COVID-19 Response Consortium, UK. Electronic address: ben.swallow@glasgow.ac.uk., Birrell P; Analytics & Data Science, UKHSA, UK; MRC Biostatistics Unit, University of Cambridge, Cambridge, UK., Blake J; MRC Biostatistics Unit, University of Cambridge, Cambridge, UK., Burgman M; Centre for Environmental Policy, Imperial College London, London, UK., Challenor P; The Alan Turing Institute, London, UK; College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK., Coffeng LE; Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands., Dawid P; Statistical Laboratory, University of Cambridge, Cambridge, UK., De Angelis D; MRC Biostatistics Unit, University of Cambridge, Cambridge, UK; Joint UNIversities Pandemic and Epidemiological Research, UK., Goldstein M; Department of Mathematical Sciences, Durham University, Stockton Road, Durham, UK., Hemming V; Department of Forest and Conservation Sciences, University of British Columbia, Vancouver, Canada., Marion G; Scottish COVID-19 Response Consortium, UK; Biomathematics and Statistics Scotland, Edinburgh, UK., McKinley TJ; College of Medicine and Health, University of Exeter, Exeter, UK; Joint UNIversities Pandemic and Epidemiological Research, UK., Overton CE; Department of Mathematics, University of Manchester, Manchester, UK; Clinical Data Science Unit, Manchester University NHS Foundation Trust, Manchester, UK; Joint UNIversities Pandemic and Epidemiological Research, UK., Panovska-Griffiths J; The Big Data Institute, University of Oxford, Oxford, UK; The Queen's College, University of Oxford, Oxford, UK., Pellis L; Department of Mathematics, University of Manchester, Manchester, UK; Joint UNIversities Pandemic and Epidemiological Research, UK; The Alan Turing Institute, London, UK., Probert W; The Big Data Institute, University of Oxford, Oxford, UK., Shea K; Department of Biology and Centre for Infectious Disease Dynamics, The Pennsylvania State University, PA 16802, USA., Villela D; Program of Scientific Computing, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil., Vernon I; Department of Mathematical Sciences, Durham University, Stockton Road, Durham, UK.
Source: Epidemics [Epidemics] 2022 Mar; Vol. 38, pp. 100547. Date of Electronic Publication: 2022 Feb 10.
Publication Type: Journal Article; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.
Journal Info: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 101484711 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1878-0067 (Electronic) Linking ISSN: 18780067 NLM ISO Abbreviation: Epidemics Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1878-0067
DOI:10.1016/j.epidem.2022.100547